Multiple dependant variable issue


#1

Is there any technique to handle a dataset with multiple dependant variables? Note: Its not about multiclass classification problem/Market Basket/Recommender Systems.

e.g. A dataset has, lets say 200 dependant variables as different products. Rows represent the customers who have bought the products. Hence a customer can buy multiple products at the same time. Is there any supervised technique to predict the probabilities for the products which customers in test dataset will buy?


#2

I feel like you may need to use recommendation engine to solve this problem.

there are types here:
1.content based filtering
2. collaborative filtering

you may need to use collaborative filtering to solve the above problem.

you can read more on this at this url : https://www.analyticsvidhya.com/blog/2018/06/comprehensive-guide-recommendation-engine-python/